Method and apparatus for analyzing text data capable of adjusting order of intention inference

Abstract

Disclosed is a method for analyzing text data, which is performed by a computing device including at least one processor. The method may include: acquiring a query text; determining a priority among a plurality of analysis modules for analyzing the query text based on priority determination information input from a user; and analyzing the query text through at least one analysis module of the plurality of analysis modules based on the determined priority.

What is claimed is: 
     
         1 . A method for analyzing text data, which is performed by a computing device including at least one processor, the method comprising:
 acquiring a query text;   determining a priority among a plurality of analysis modules for analyzing the query text based on priority determination information input from a user; and   analyzing the query text through at least one analysis module of the plurality of analysis modules based on the determined priority.   
     
     
         2 . The method of  claim 1 , wherein the plurality of analysis modules include at least two of a pattern matching module, a morpheme analysis module, a language rule based analysis module, or a deep learning based analysis module. 
     
     
         3 . The method of  claim 2 , wherein the pattern matching module analyzes the query text based on one or more pattern matching degrees calculated by matching a pattern of the query text and each of patterns of one or more existing texts prestored. 
     
     
         4 . The method of  claim 2 , wherein the analyzing of the query text through the morpheme analysis module includes
 acquiring a morpheme analysis result for the query text through the morpheme analysis module, and   analyzing the query text based on the morpheme analysis result for the query text and a morpheme analysis result for at least one existing text.   
     
     
         5 . The method of  claim 4 , wherein the analyzing of the query text based on the morpheme analysis result for the query text and the morpheme analysis result for at least one existing text includes
 calculating a first similarity between the morpheme analysis result for the query text and the morpheme analysis result for at least one existing text,   calculating one or more candidate texts from the at least one existing text based on the first similarity, and   analyzing the query text based on a second similarity calculated between the query text and the one or more candidate texts.   
     
     
         6 . The method of  claim 5 , wherein the first similarity is calculated based on one or more term frequencies commonly included in the morpheme analysis result for the query text and the morpheme analysis result for the at least one existing text, and
 the second similarity is calculated based on a common character between the query text and the one or more candidate texts.   
     
     
         7 . The method of  claim 2 , wherein the language rule based analysis module analyzes the query text based on a language rule set including at least one language rule. 
     
     
         8 . The method of  claim 7 , wherein the language rule is generated based on association information calculated for one or more existing texts based on concept information. 
     
     
         9 . The method of  claim 1 , wherein the priority determination information includes
 order information for determining an application order of the plurality of analysis modules for the query text, or   a threshold for at least one analysis accuracy of analysis accuracies for the plurality of respective analysis modules.   
     
     
         10 . The method of  claim 1 , further comprising:
 providing a user interface for receiving the priority determination information from a user.   
     
     
         11 . The method of  claim 10 , wherein the user interface includes at least one of an icon for each of the plurality of analysis modules of which the priority is determined according to a position on a display screen, the analysis accuracy for each of the plurality of analysis modules, and a threshold input field for the analysis accuracy. 
     
     
         12 . The method of  claim 11 , wherein in the user interface,
 when the analysis accuracy of a deep learning based analysis module is less than a predetermined value,   the icon for the pattern matching module is positioned to have a higher priority than the icon for the deep learning based analysis module, and   when the analysis accuracy of the deep learning based analysis module is equal to or higher than the predetermined value,   the icon for the deep learning based analysis module is positioned to have a higher priority than the icon for the pattern matching module.   
     
     
         13 . A non-transitory computer readable medium including a computer program, wherein the computer program executes the following operations for analyzing text data when the computer program is executed by one or more processors, the operations comprising:
 acquiring a query text;   determining a priority among a plurality of analysis modules for analyzing the query text based on priority determination information input from a user; and   analyzing the query text through a plurality of analysis modules according to the determined priority.   
     
     
         14 . An apparatus for analyzing text data, the apparatus comprising:
 one or more processors;   a memory; and   a network,   wherein the one or more processors are configured to:   acquire a query text,   determine a priority among a plurality of analysis modules for analyzing the query text based on priority determination information input from a user; and   analyze the query text through the plurality of analysis modules according to the determined priority.